Top Tech Jobs & Startup Jobs in NYC, NY

As an AI Research Engineer, you'll conduct research in AI and automated reasoning, creating innovative solutions, testing systems, and contributing to scientific publications while collaborating with engineering teams.

Lead end-to-end pipeline generation across field, channel, digital, partner, and SDR teams. Build and scale demand programs (ABM, outbound, events, inbound, paid), define lead-to-SQL model, track funnel metrics, partner with Sales/RevOps/Finance/Partnerships, and run weekly optimization loops. Hire and develop a demand team and launch integrated plays to scale qualified enterprise pipeline.

Build and scale backend services and integrations for autonomous AI agents. Design distributed, stateless and stateful systems, APIs, and infrastructure for reliability, security, and enterprise integration. Drive scalability, CI/CD, container orchestration, multi-cloud deployments, and mentor growing engineering teams.

Build and own Cogent's full‑stack AI security product experience: design, implement, and maintain backend microservices, APIs and databases; develop frontend interfaces (customer portal, knowledge engine, labeling tool, dashboards); integrate systems; ship features in a multi‑tenant/cloud environment; mentor hires and contribute to engineering, operational excellence, and hiring processes.

Lead frontend architecture and platform work, build reusable component libraries and tooling, deliver AI-driven user features for security workflows, mentor engineers, and ensure scalable, high-quality frontend infrastructure and UX.

Design and build agentic AI systems for cybersecurity: architect AI cyber taskforce and production-grade agentic components, implement ranking/retrieval/search powered by LLMs, design training/evaluation frameworks, decompose security workflows, address scale/performance, and mentor engineers while contributing to engineering and operational excellence.

Design and implement a scalable data platform and integration pipeline to ingest, normalize, and index enterprise data. Build connectors, ETL/streaming pipelines, and storage/indexing strategies to support semantic search and GenAI use cases. Partner with applied AI teams, make build-vs-buy decisions, and create reusable patterns to scale integrations.

Own and build the software delivery lifecycle and CI/CD/platform systems that enable engineers and autonomous agents to build, test, deploy, and verify code securely. Implement self-hosted builders, secure GitHub Actions Runner alternatives, and infrastructure provisioning solutions.

Build and optimize data platform storage (ClickHouse, Postgres), enable on-prem deployments for enterprise customers, harden security systems, create an agent-first infrastructure and platform layer, and lead large-scale infrastructure projects across stakeholders.

Own storage, protection, and operations for relational, streaming, and analytical stores. Standardize backup, restore, retention, and encryption across Aurora/RDS, ClickHouse, and MSK. Build observability dashboards for capacity, performance, replication, lag, and cost. Create a Storage Operations Agent for incident triage, slow-query investigation, and remediation workflows. Hands-on engineering role focused on data infrastructure, automation, and agent-forward operations.